Some techniques for performing computer vision tasks such as image object recognition use a trained machine learning model. The model typically is trained based upon the attributes that belong to each object in an image, such as color, curves, and the like, by providing the model with labeled training data. Based on the labeled training data, the model may learn that, for example, a grey object that is curved on one end and contains a trunk-like shape on the other end is most likely an elephant. The trained model is then provided with non-labeled images, in which the model attempts to identify and label objects based on the prior training.